Churchill Downs Incorporated (CHDN)
the evolution of cdi cdi’s history is well known. its namesake racetrack, churchill downs, in louisville, ky., opened in 1875 and during its inaugural race meeting featured two races, the kentucky derby and kentucky oaks, which still highlight churchill downs’ live racing calendar today. today, the twin spires still proudly reign over churchill downs’ homestretch, and kentucky derby champions race by these architectural features turned trademarks on their way to the finish line, the winner’s circle and the history books. about churchill downs incorporated churchill downs incorporated (cdi) (nasdaq: chdn), headquartered in louisville, ky., owns the world-renowned churchill downs racetrack, home of the kentucky derby and kentucky oaks, as well as racetrack and casino operations in miami gardens, fla.; racetrack, casino and video poker operations in new orleans, la.; racetrack operations in arlington heights, ill.; a casino resort in greenville, miss.; a casino hotel in vicksburg,
Stock Price Trends
Stock price trends estimated using linear regression.
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Key facts
- The primary trend is increasing.
- The growth rate of the primary trend is 6.84% per annum.
- CHDN price at the close of December 8, 2023 was $119.89 and was inside the primary price channel.
- The secondary trend is decreasing.
- The decline rate of the secondary trend is 35.50% per annum.
- CHDN price at the close of December 8, 2023 was higher than the top border of the secondary price channel by $0.93 (0.78%). This indicates a possible reversal in the secondary trend direction.
- The direction of the secondary trend is opposite to the direction of the primary trend. This indicates a possible reversal in the direction of the primary trend.
Linear Regression Model
Model equation:
Yi = α + β × Xi + εi
Top border of price channel:
Exp(Yi) = Exp(a + b × Xi + 2 × s)
Bottom border of price channel:
Exp(Yi) = Exp(a + b × Xi – 2 × s)
where:
i - observation number
Yi - natural logarithm of CHDN price
Xi - time index, 1 day interval
σ - standard deviation of εi
a - estimator of α
b - estimator of β
s - estimator of σ
Exp() - calculates the exponent of e
Primary Trend
Start date:
End date:
a =
b =
s =
Annual growth rate:
Exp(365 × b) – 1
= Exp(365 × ) – 1
=
Price channel spread:
Exp(4 × s) – 1
= Exp(4 × ) – 1
=
November 13, 2020 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $
December 8, 2023 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $
Secondary Trend
Start date:
End date:
a =
b =
s =
Annual growth rate:
Exp(365 × b) – 1
= Exp(365 × ) – 1
=
Price channel spread:
Exp(4 × s) – 1
= Exp(4 × ) – 1
=
April 27, 2023 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $
December 8, 2023 calculations
Top border of price channel:
Exp(Y)
= Exp(a + b × X + 2 × s)
= Exp(a + b × + 2 × s)
= Exp( + × + 2 × )
= Exp()
= $
Bottom border of price channel:
Exp(Y)
= Exp(a + b × X – 2 × s)
= Exp(a + b × – 2 × s)
= Exp( + × – 2 × )
= Exp()
= $